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bayesreg: Bayesian Regression Models with Global-Local Shrinkage Priors
Fits linear or generalized linear regression models using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) <doi:10.1093/acprof:oso/9780199694587.003.0017>. Provides an efficient implementation of ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace, Student-t, Poisson or geometric distributed targets using the algorithms summarized in Makalic and Schmidt (2016) <arXiv:1611.06649>.
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Package details |
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| Author | Daniel F. Schmidt [aut, cph, cre] (<https://orcid.org/0000-0002-1788-2375>), Enes Makalic [aut, cph] (<https://orcid.org/0000-0003-3017-0871>) |
| Maintainer | Daniel F. Schmidt <daniel.schmidt@monash.edu> |
| License | GPL (>= 3) |
| Version | 1.2 |
| Package repository | View on CRAN |
| Installation |
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